Comparing ‘Top’ and Local Universities in Ukraine

Oleksandr Koval

Introduction

Story of Creating

Why did I create this presentation?
There are lots of opportunities to continue your education nowadays. If you used to have only a few main universities to attend, now almost every region has its local universities offering different specializations. So, where would you go?

“TOP UNIVERSITIES” VS LOCAL UNIVERSITY

Short introduction

As a top university, I took three of the biggest Ukrainian national universities that have a strong base of all specializations. As a local one, I took polytechnic universities that are located in the big cities of Ukraine (Dnipro, Odesa, Vinnytsia) but we can’t name them “top”.

OUR GUESTS

Team “TOP UNIVERSITIES”:

  • KPI
  • KNUTS
  • LKPI

Team “Local universities”:

  • VNTU
  • NTUDP
  • NUOPL

Location

Map of key “Top” and Local Universities in Ukraine

By the end, we want to know…

  • Is a “top” university really worth it ?
  • Where would be better to go ?
  • Why “top” university is “Top” ?
  • Is a local university worth it ?
  • Where will you find your dream ?

Data overview

Data Overview

All information was taken from 1-scribe

It contains all used data in this presentation

Data Overview

Source: 1-scribe-ds3.rds
Main table: ds3
Rows: 200
Columns: 36
Columns that we use: rank_2024, qs_rank, scopus_rank, webometrics_rank, wur_rank, qswur_rank, school_abb, student_count, city, application_total_count, application_budget_count, score_mean

Data Overview

ds3 - data %>% glimpse()

Rows: 201
Columns: 36
$ school_id                <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
$ school_name              <chr> "Національний  технічний  університет  Україн…
$ rank_2024                <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14…
$ index_2024               <dbl> 4.66, 4.94, 5.14, 5.93, 5.98, 7.43, 11.12, 11…
$ qs_rank                  <dbl> 3, 1, 4, 2, 4, 5, 6, 4, 5, 5, 7, 7, 4, 7, 7, …
$ qs_index                 <dbl> 0.45, 0.15, 0.60, 0.30, 0.60, 0.75, 0.90, 0.6…
$ scopus_rank              <dbl> 5, 1, 9, 2, 6, 3, 21, 11, 4, 24, 30, 7, 23, 3…
$ scopus_index             <dbl> 0.65, 0.13, 1.17, 0.26, 0.78, 0.39, 2.73, 1.4…
$ webometrics_rank         <dbl> 1, 3, 11, 9, 2, 10, 6, 8, 32, 7, 20, 15, 37, …
$ webometrics_index        <dbl> 0.1, 0.3, 1.1, 0.9, 0.2, 1.0, 0.6, 0.8, 3.2, …
$ uimpact_rank             <dbl> 5, 6, 2, 4, 1, 5, 6, 4, 4, 4, 6, 5, 6, 4, 6, …
$ uimpact_index            <dbl> 0.625, 0.750, 0.250, 0.500, 0.125, 0.625, 0.7…
$ wur_rank                 <dbl> 4, 4, 2, 4, 1, 4, 5, 4, 6, 3, 6, 4, 6, 6, 6, …
$ wur_index                <dbl> 0.60, 0.60, 0.30, 0.60, 0.15, 0.60, 0.75, 0.6…
$ qswur_rank               <dbl> 4, 6, 1, 3, 2, 5, 9, 7, 9, 8, 9, 9, 9, 9, 9, …
$ qswur_index              <dbl> 0.500, 0.750, 0.125, 0.375, 0.250, 0.625, 1.1…
$ competition_rank         <dbl> 1, 3, 2, 8, 4, 5, 7, 16, 11, 30, 9, 14, 13, 2…
$ competition_index        <dbl> 0.055, 0.165, 0.110, 0.440, 0.220, 0.275, 0.3…
$ naqa_rank                <dbl> 1, 2, 3, 10, 8, 7, 4, 66, 9, 28, 6, 78, 13, 1…
$ naqa_index               <dbl> 0.055, 0.110, 0.165, 0.550, 0.440, 0.385, 0.2…
$ patent_rank              <dbl> 5, 16, 2, 17, 14, 27, 4, 11, 32, 24, 21, 28, …
$ patent_index             <dbl> 0.275, 0.880, 0.110, 0.935, 0.770, 1.485, 0.2…
$ mean_rank                <dbl> 24.5, 20.0, 22.0, 19.5, 44.5, 23.5, 62.5, 30.…
$ mean_index               <dbl> 1.348, 1.100, 1.210, 1.073, 2.448, 1.293, 3.4…
$ school_abb               <chr> "KPI", "KNUTS", "LKPI", "HNUK", "SSU", "LNU",…
$ student_count            <dbl> 40500, 25000, 35000, 16000, 14000, 19357, 390…
$ city                     <chr> "Kyiv", "Kyiv", "Lviv", "Kharkiv", "Sumy", "L…
$ oblast                   <chr> "Kyiv", "Kyiv", "Lviv", "Kharkiv", "Sumy", "L…
$ region                   <chr> "North", "North", "West", "East", "North", "W…
$ profile                  <chr> "polytechnic", "general", "polytechnic", "gen…
$ department_count         <dbl> 19, 14, 16, 21, 8, 19, 13, 10, 11, 8, 9, 12, …
$ program_count            <dbl> 118, 198, 64, 115, 55, 198, 32, 90, 44, 25, 4…
$ city_population          <dbl> 3020000, 3020000, 721301, 1418980, 271000, 72…
$ application_total_count  <dbl> 30156, 29812, 31641, 11206, 4075, 31190, 1033…
$ score_mean               <dbl> 159.3, 162.3, 160.0, 164.1, 161.1, 159.4, 148…
$ application_budget_count <dbl> 21488, 19616, 21969, 7261, 2991, 21576, 6622,…

Data Overview

ds3 - data %>% summary()

   school_id     school_name          rank_2024       index_2024   
 Min.   :  1.0   Length:201         Min.   :  1.0   Min.   : 4.66  
 1st Qu.: 51.0   Class :character   1st Qu.: 51.0   1st Qu.:28.00  
 Median :101.0   Mode  :character   Median :101.0   Median :42.60  
 Mean   :100.6                      Mean   :100.6   Mean   :40.30  
 3rd Qu.:150.0                      3rd Qu.:150.0   3rd Qu.:53.34  
 Max.   :200.0                      Max.   :200.0   Max.   :66.42  
                                                                   
    qs_rank         qs_index      scopus_rank     scopus_index  
 Min.   :1.000   Min.   :0.150   Min.   :  1.0   Min.   : 0.13  
 1st Qu.:7.000   1st Qu.:1.050   1st Qu.: 51.0   1st Qu.: 6.63  
 Median :7.000   Median :1.050   Median :101.0   Median :13.13  
 Mean   :6.831   Mean   :1.025   Mean   :101.7   Mean   :13.22  
 3rd Qu.:7.000   3rd Qu.:1.050   3rd Qu.:150.0   3rd Qu.:19.50  
 Max.   :7.000   Max.   :1.050   Max.   :202.0   Max.   :26.26  
                                                                
 webometrics_rank webometrics_index  uimpact_rank   uimpact_index   
 Min.   :  1.0    Min.   : 0.10     Min.   :1.000   Min.   :0.1250  
 1st Qu.: 51.0    1st Qu.: 5.10     1st Qu.:6.000   1st Qu.:0.7500  
 Median :101.0    Median :10.10     Median :6.000   Median :0.7500  
 Mean   :102.6    Mean   :10.26     Mean   :5.657   Mean   :0.7071  
 3rd Qu.:150.0    3rd Qu.:15.00     3rd Qu.:6.000   3rd Qu.:0.7500  
 Max.   :236.0    Max.   :23.60     Max.   :6.000   Max.   :0.7500  
                                                                    
    wur_rank       wur_index        qswur_rank     qswur_index   
 Min.   :1.000   Min.   :0.1500   Min.   :1.000   Min.   :0.125  
 1st Qu.:6.000   1st Qu.:0.9000   1st Qu.:9.000   1st Qu.:1.125  
 Median :6.000   Median :0.9000   Median :9.000   Median :1.125  
 Mean   :5.846   Mean   :0.8769   Mean   :8.821   Mean   :1.103  
 3rd Qu.:6.000   3rd Qu.:0.9000   3rd Qu.:9.000   3rd Qu.:1.125  
 Max.   :6.000   Max.   :0.9000   Max.   :9.000   Max.   :1.125  
                                                                 
 competition_rank competition_index   naqa_rank        naqa_index   
 Min.   : 1.0     Min.   :0.055     Min.   :  1.00   Min.   :0.055  
 1st Qu.:27.0     1st Qu.:1.485     1st Qu.: 46.00   1st Qu.:2.530  
 Median :31.0     Median :1.705     Median : 77.00   Median :4.235  
 Mean   :29.7     Mean   :1.633     Mean   : 82.16   Mean   :4.519  
 3rd Qu.:36.0     3rd Qu.:1.980     3rd Qu.:120.00   3rd Qu.:6.600  
 Max.   :36.0     Max.   :1.980     Max.   :163.00   Max.   :8.965  
                                                                    
  patent_rank     patent_index     mean_rank        mean_index    
 Min.   : 1.00   Min.   :0.055   Min.   : 19.50   Min.   : 1.073  
 1st Qu.:29.00   1st Qu.:1.595   1st Qu.: 68.50   1st Qu.: 3.768  
 Median :36.00   Median :1.980   Median : 94.00   Median : 5.170  
 Mean   :31.21   Mean   :1.717   Mean   : 95.22   Mean   : 5.237  
 3rd Qu.:37.00   3rd Qu.:2.035   3rd Qu.:120.00   3rd Qu.: 6.600  
 Max.   :37.00   Max.   :2.035   Max.   :201.00   Max.   :11.055  
                                                                  
  school_abb        student_count       city              oblast         
 Length:201         Min.   :  178   Length:201         Length:201        
 Class :character   1st Qu.: 4000   Class :character   Class :character  
 Mode  :character   Median : 6000   Mode  :character   Mode  :character  
                    Mean   : 8371                                        
                    3rd Qu.:10000                                        
                    Max.   :40500                                        
                    NA's   :4                                            
    region            profile          department_count program_count   
 Length:201         Length:201         Min.   : 5.00    Min.   :  6.00  
 Class :character   Class :character   1st Qu.: 6.00    1st Qu.: 25.00  
 Mode  :character   Mode  :character   Median : 8.00    Median : 35.00  
                                       Mean   : 9.32    Mean   : 46.30  
                                       3rd Qu.:11.00    3rd Qu.: 54.75  
                                       Max.   :21.00    Max.   :198.00  
                                       NA's   :151      NA's   :151     
 city_population   application_total_count   score_mean   
 Min.   :  24000   Min.   :   53.0         Min.   :139.5  
 1st Qu.: 271000   1st Qu.:  931.2         1st Qu.:147.3  
 Median : 721301   Median : 2152.0         Median :151.3  
 Mean   :1131621   Mean   : 3531.8         Mean   :153.5  
 3rd Qu.:1418980   3rd Qu.: 3964.2         3rd Qu.:157.7  
 Max.   :3020000   Max.   :31641.0         Max.   :193.3  
                   NA's   :7               NA's   :8      
 application_budget_count
 Min.   :   39.0         
 1st Qu.:  610.5         
 Median : 1443.0         
 Mean   : 2499.4         
 3rd Qu.: 3017.5         
 Max.   :21969.0         
 NA's   :34              

Rating system

Chapters of this presentation

  • 🌍 The importance of location
  • 📝 Chances to get in
  • 🏆 National rank
  • 🏙️ Local university comparison:
    • Local rank
    • Local size
    • Local score to apply
  • 🌐 International attitude

1 | The importance of location

Imagine that you just graduated from school. You passed your exams very well.
The first thing you note when you are looking at your future university is the city, where it’s located.

Map of the Local Universities

Why it is so important?

Your university city is not just about education – it’s your lifestyle for 4–6 years.


Think about how you will live without your friends and family.


What would you do if something went wrong?

Are you the kind of person who can make new friends quickly, or not?

PROS & CONS BIG CITY

Think logically: Big city = big opportunities

  • In a big city, there are more chances to be noticed by big or international companies

  • Universities are more modern, with stronger academic programs

  • Risk of “getting lost in the crowd”

  • Expensive accommodation, food, and entertainment

  • Higher competition for entry and during studies, making it harder to stand out

PROS & CONS LIVING HOME

It is your home!

  • Familiar city, close to your family and friends. They can help you and support you in trouble
  • You haven’t got a “period of adaptation” or it would be far shorter than in a big city
  • You may have “the feeling of missed opportunity”
  • You have fewer contacts with international companies
  • Less perspective than in a big city

Overall

Living in a big city can be hard, and for some people, it can be very difficult to meet new friends or live alone. However, for everyone, it is a very useful experience that absolutely must be felt by all young adults.

Living in your hometown is easier, and you don’t need to make as much effort in your daily life. It is more stable.

2 | Chances to get in

The second thing you check after considering the city is whether you have the opportunity to become part of the team.

How many other people are thinking the same as you?

What if you are short of money?

Will your average score be enough?

№1 Total number of applications

№2 Number of applications on Budget

№3 Number of budget applications to non-budget

№3-1 Number of budget applications to non-budget

№4 The average score

3 | National Rank

What is it?

The national rank according to EuroOsvita is the most authoritative rank in the country. We have over 200 universities in this rank. This rank is based on different ranks, including foreign and national.

“Top” Universities VS Local

4 | Comparing Locally

When you have checked your chances to get in and seen the big picture, what do you want to do next?

In my opinion, it’s a good idea to consider other university options in your city.

In this chapter, we compare all universities in Odesa, Vinnytsia, and Dnipro.

Universities in the Vinnytsia | EuroOsvita

Universities in the Vinnytsia | Number of Students

Universities in the Vinnytsia | Average score

In Odesa

Universities in the Odesa | EuroOsvita

Universities in the Odesa | Number of Students

Universities in the Odesa | Average score

In Dnipro

Universities in the Dnipropetrovsk | EuroOsvita

Universities in the Dnipropetrovsk | Number of Students

Universities in the Dnipropetrovsk | Average Score

4 | International Attitude

What is it?

The last thing that can insure you to apply is the international attitude. We are going to compare universities by different international ranks (that are already included in the main “National Rank”).

We are comparing according to:

  • Scopus Rank
  • QS Rank
  • Webometrics Rank
  • THE World University Ranking
  • QS Sustainability Ranking

Scopus Rank

Qs Rank

Webometrics Rank

The World University Ranking

QS Sustainability Ranking

Summary

Honestly, it is so hard to choose one university. This is a very important decision in your life that will determine the next 4–5 years of your life, your future friends, and possibly your whole future career. It sounds very serious, doesn’t it?

The author of this presentation advises all students who don’t know which university to choose: you have already seen all the advantages and disadvantages, all the info about locations, rankings, and other analytics—so just choose how you feel/